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  1. The Influence of Values on Medical Research.S. Andrew Schroeder - forthcoming - In Alex Broadbent (ed.), Oxford Handbook of Philosophy of Medicine. Oxford University Press.
    Mainstream views of medical research tell us it should be a fact-based, value-free endeavor: what a scientist (or her funding source) wants or cares about should not influence her findings. At the same time, we also sometimes criticize medical research for failing to embody certain values, e.g. when we criticize pharmaceutical companies for largely ignoring the diseases that affect the global poor. This chapter seeks to reconcile these perspectives by distinguishing appropriate from inappropriate influences of values on medical research. It (...)
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  • The Difference-to-Inference Model for Values in Science.Jacob Stegenga & Tarun Menon - 2023 - Res Philosophica 100 (4):423-447.
    The value-free ideal for science holds that values should not influence the core features of scientific reasoning. We defend the difference-to-inference model of value-permeation, which holds that value-permeation in science is problematic when values make a difference to the inferences made about a hypothesis. This view of value-permeation is superior to existing views, and it suggests a corresponding maxim—namely, that scientists should strive to eliminate differences to inference. This maxim is the basis of a novel value-free ideal for science. -/- (...)
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  • Transparency is Surveillance.C. Thi Nguyen - 2021 - Philosophy and Phenomenological Research 105 (2):331-361.
    In her BBC Reith Lectures on Trust, Onora O’Neill offers a short, but biting, criticism of transparency. People think that trust and transparency go together but in reality, says O'Neill, they are deeply opposed. Transparency forces people to conceal their actual reasons for action and invent different ones for public consumption. Transparency forces deception. I work out the details of her argument and worsen her conclusion. I focus on public transparency – that is, transparency to the public over expert domains. (...)
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  • The New Worries about Science.Janet A. Kourany - 2022 - Canadian Journal of Philosophy 52 (3):227-245.
    Science is based onfacts—facts that are systematically gathered by a community of enquirers through detailed observation and experiment. In the twentieth century, however, philosophers of science claimed that the facts that scientists “gather” in this way are shaped by the theories scientists accept, and this seemed to threaten the authority of science. Call this theold worries about science.By contrast, what seemed not to threaten that authority were other factors that shaped the facts that scientists gather—for example, the mere questions scientists (...)
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  • The Value of ‘Traditionality’: The Epistemological and Ethical Significance of Non-western Alternatives in Science.Mahdi Kafaee & Mostafa Taqavi - 2021 - Science and Engineering Ethics 27 (1):1-20.
    After a brief review of the relationship between science and value, this paper introduces the value of ‘traditionality’ as a value in the pure and applied sciences. Along with other recognized values, this value can also contribute to formulating hypotheses and determining theories. There are three reasons for legitimizing the internal role of this value in science: first, this value can contribute to scientific progress by presenting more diverse hypotheses; second, the value of external consistency in science entails this value; (...)
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  • Understanding the Problem of “Hype”: Exaggeration, Values, and Trust in Science.Kristen Intemann - 2022 - Canadian Journal of Philosophy 52 (3):279-294.
    Several science studies scholars report instances of scientific “hype,” or sensationalized exaggeration, in journal articles, institutional press releases, and science journalism in a variety of fields (e.g., Caulfield and Condit 2012). Yet, how “hype” is being conceived varies. I will argue that hype is best understood as a particular kind of exaggeration, one that explicitly or implicitly exaggerates various positive aspects of science in ways that undermine the goals of science communication in a particular context. This account also makes clear (...)
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  • Science Advice in an Environment of Trust: Trusted, but Not Trustworthy?Torbjørn Gundersen & Cathrine Holst - 2022 - Social Epistemology 36 (5):629-640.
    This paper examines the conditions of trustworthy science advice mechanisms, in which scientists have a mandated role to inform public policymaking. Based on the literature on epistemic trust and public trust in science, we argue that possession of relevant expertise, justified moral and political considerations, as well as proper institutional design are conditions for trustworthy science advice. In order to assess these conditions further, we explore the case of temporary advisory committees in Norway. These committees exemplify a de facto trusted (...)
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  • Fake News vs. Echo Chambers.Jeremy Fantl - 2021 - Social Epistemology 35 (6):645-659.
    I argue that there is a prima facie tension between solutions to the problem of fake news and solutions to the problem presented by various cognitive biases that dispose us to dismiss evidence against our prior beliefs (what might seem to be the driving force behind echo chambers). We can guard against fake news by strengthening belief. But we can exit echo chambers by becoming more sensitive to counterevidence, which seems to require weakening our beliefs. I resolve the tension by (...)
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  • The value-ladenness of transparency in science: Lessons from Lyme disease.Kevin C. Elliott - 2021 - Studies in History and Philosophy of Science Part A 88 (C):1-9.
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  • Addressing the Reproducibility Crisis: A Response to Hudson.Heather Douglas & Kevin C. Elliott - 2022 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 53 (2):201-209.
    In this response to Robert Hudson’s article, “Should We Strive to Make Science Bias-Free? A Philosophical Assessment of the Reproducibility Crisis,” we identify three ways in which he misrepresents our work: he conflates value-ladenness with bias; he describes our view as one in which values are the same as evidential factors; and he creates a false dichotomy between two ways that values could be considered in science for policy. We share Hudson’s concerns about promoting scientific reproducibility and reducing bias in (...)
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  • How can we assess whether to trust collectives of scientists?Elinor Clark - forthcoming - British Journal for the Philosophy of Science.
    A great many important decisions we make in life depend on scientific information that we are not in a position to assess. So it seems we must defer to experts. By now there are a variety of criteria on offer by which non-experts can judge the trustworthiness of a scientist responsible for producing or promulgating this information. But science is, for the most part, a collective not an individual enterprise. This paper explores which of the criteria for judging the trustworthiness (...)
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  • Group intellectual transparency: a novel case for non-summativism.T. Ryan Byerly - 2022 - Synthese 200 (2):1-22.
    Philosophical reflection on transparency, including group transparency, is beginning to gain steam. This paper contributes to this work by developing a conceptualization of transparency as an intellectual character trait that groups can possess, and by presenting a novel argument for thinking that such transparency should be understood along non-summativist lines. According to the account offered, a group’s being intellectually transparent consists in the group’s tending to attend well to its perspective and to share its perspective faithfully with others in order (...)
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  • Intellectual Honesty and Intellectual Transparency.T. Ryan Byerly - 2023 - Episteme 20 (2):410-428.
    The purpose of this paper is to advance understanding of intellectually virtuous honesty, by examining the relationship between a recent account of intellectual honesty and a recent account of intellectual transparency. The account of intellectual honesty comes from Nathan King, who adapts the work of Christian Miller on moral honesty, while the account of intellectual transparency comes from T. Ryan Byerly. After introducing the respective accounts, I identify four potential differences between intellectual honesty and intellectual transparency as understood by these (...)
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  • How to Philosophically Tackle Kinds without Talking About ‘Natural Kinds’.Ingo Brigandt - 2022 - Canadian Journal of Philosophy 52 (3):356-379.
    Recent rival attempts in the philosophy of science to put forward a general theory of the properties that all (and only) natural kinds across the sciences possess may have proven to be futile. Instead, I develop a general methodological framework for how to philosophically study kinds. Any kind has to be investigated and articulated together with the human aims that motivate referring to this kind, where different kinds in the same scientific domain can answer to different concrete aims. My core (...)
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  • Engaging with science, values, and society: introduction.Ingo Brigandt - 2022 - Canadian Journal of Philosophy 52 (3):223-226.
    Philosophical work on science and values has come to engage with the concerns of society and of stakeholders affected by science and policy, leading to socially relevant philosophy of science and socially engaged philosophy of science. This special issue showcases instances of socially relevant philosophy of science, featuring contributions on a diversity of topics by Janet Kourany, Andrew Schroeder, Alison Wylie, Kristen Intemann, Joyce Havstad, Justin Biddle, Kevin Elliott, and Ingo Brigandt.
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  • On Predicting Recidivism: Epistemic Risk, Tradeoffs, and Values in Machine Learning.Justin B. Biddle - 2022 - Canadian Journal of Philosophy 52 (3):321-341.
    Recent scholarship in philosophy of science and technology has shown that scientific and technological decision making are laden with values, including values of a social, political, and/or ethical character. This paper examines the role of value judgments in the design of machine-learning systems generally and in recidivism-prediction algorithms specifically. Drawing on work on inductive and epistemic risk, the paper argues that ML systems are value laden in ways similar to human decision making, because the development and design of ML systems (...)
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  • Fast Science.Jacob Stegenga - forthcoming - The British Journal for the Philosophy of Science.
    If scientists violate principles and practices of routine science to quickly develop interventions against catastrophic threats, they are engaged in what I call fast science. The magnitude, imminence, and plausibility of a threat justify engaging in and acting on fast science. Yet, that justification is incomplete. I defend two principles to assess fast science, which say: fast science should satisfy as much as possible the reliability-enhancing features of routine science, and the fast science developing an intervention against a threat should (...)
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